Pruning Points Detection of Sweet Pepper Plants Using 3D Point Clouds and Semantic Segmentation Neural Network [PDF]
Sensors, 2023 Automation in agriculture can save labor and raise productivity. Our research aims to have robots prune sweet pepper plants automatically in smart farms.
Truong Thi Huong Giang, Young-Jae Ryoo
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PFuji-Size dataset: A collection of images and photogrammetry-derived 3D point clouds with ground truth annotations for Fuji apple detection and size estimation in field conditions [PDF]
Data in Brief, 2021 The PFuji-Size dataset is comprised of a collection of 3D point clouds of Fuji apple trees (Malus domestica Borkh. cv. Fuji) scanned at different maturity stages and annotated for fruit detection and size estimation.
Jordi Gené-Mola +4 more
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SIMULATING LIDAR TO CREATE TRAINING DATA FOR MACHINE LEARNING ON 3D POINT CLOUDS [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 3D point clouds represent an essential category of geodata used in a variety of geoinformation applications. Typically, these applications require additional semantics to operate on subsets of the data like selected objects or surface categories. Machine
J. Hildebrand +3 more
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IMAGE TO POINT CLOUD TRANSLATION USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORK FOR AIRBORNE LIDAR DATA [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 This study introduces a novel image to a 3D point-cloud translation method with a conditional generative adversarial network that creates a large-scale 3D point cloud.
T. Shinohara, H. Xiu, M. Matsuoka
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Remote Sensing, 2023 Change detection (CD) is a technique widely used in remote sensing for identifying the differences between data acquired at different times. Most existing 3D CD approaches voxelize point clouds into 3D grids, project them into 2D images, or rasterize ...
Ming Han +3 more
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CHANGE DETECTION OF TIME-SERIES 3D POINT CLOUDS USING ROBUST PRINCIPAL COMPONENT ANALYSIS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 The chances of acquiring three-dimensional (3D) point clouds have recently increased with the emergence of laser scanners. Hence, 3D monitoring of various objects through the accumulation of “time-series 3D point clouds,” which are point clouds of the ...
T. Fuse, T. Yamano
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Rethinking of learning-based 3D keypoints detection for large-scale point clouds registration
International Journal of Applied Earth Observations and Geoinformation, 2022 The main solution for large-scale point clouds registration is to first obtain a set of matched 3D keypoint pairs and then accomplish the point cloud registration task based on these matched keypoint pairs.
ShaoCong Liu +7 more
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Automatic Pairwise Coarse Registration of Terrestrial Point Clouds Using 3D Line Features
IEEE Access, 2022 The fully automatic registration of 3D terrestrial laser scanning (TLS) point clouds, which is the first step in the usage of point clouds, is a highly challenging task in Light Detection and Ranging (LiDAR) remote sensing applications.
Yongjian Fu +5 more
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APPLICATION OF A SHELLNET BASED APPROACH TO SEMANTIC SEGMENTATION IN URBAN POINT CLOUD [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 In recent years, the popularity of airborne, vehicle-borne, and terrestrial 3D laser scanners has driven the rapid development of 3D point cloud processing methods.
D. Chen, X. Ma, X. Lu, J. Xiao
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EDC-Net: Edge Detection Capsule Network for 3D Point Clouds
Applied Sciences, 2021 Edge features in point clouds are prominent due to the capability of describing an abstract shape of a set of points. Point clouds obtained by 3D scanner devices are often immense in terms of size. Edges are essential features in large scale point clouds
Dena Bazazian, M. Eulàlia Parés
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